watched rain man for the first time, laughed at "i think ray is in the room" and "quantas never crashed" - it still hasn't.

work while everyone else sleeps. the computer programming night shift.

received an unexpected thank you..

..and another.

confirmed that the median calculation of my dozen cheap compasses still works out to north.

read the signal and the noise..

there was "nothing new under the sun," as the beautiful bible verses in ecclesiastes put it-not so much because everything had been discovered but because everything would be forgotten

as if the weather forecast had been 86 degrees and sunny, and instead there was a blizzard

practice in weighing different types of information together

during a given season, a true .275 hitter has about a 10 percent chance of hitting .300 and a 10 percent chance of hitting .250 on the basis of luck alone

a case of uncertainty trumping risk

in complex systems, however, mistakes are not measured in degrees but in whole orders of magnitude

olympic gymnasts peak in their teens; poets in their twenties; chess players in their thirties; applied economists in their forties, and the average age of a fortune 500 ceo is 55

according to the agency's statistics, humans improve the accuracy of precipitation forecasts by about 25 percent over the computer guidance alone, and temperature forecasts by about 10 percent. moreover..these ratios have been relatively constant over time: as much progress as the computers have made, his forecasters continue to add value on top of it

i can go to wunderground.com, for instance, and tell you that the weather at 7 a.m. in lansing, michigan, on january 13, 1978-the date and time when i was born-was 18 degrees with light snow and winds from the notheast. but relatively few people had bothered to collect information on past weather forecasts

the for-profit weather forecasters rarely predict exactly a 50 percent chance of rain, which might seem wishy-washy and indecisive to consumers. instead, they'll flip a coin and round up to 60, or down to 40, even though this makes the forecasts both less accurate and less honest

the monkey who typed shakespeare; the octopus who predicted the world cup

1. a prediction is a definitive and specific statement about when and where an earthquake will strike: a major earthquake will hit kyoto, japan, on june 28.2. whereas a forecast is a probabilistic statement, usually over a longer time scale: there is a 60 percent chance of an earthquake in southern california over the next thirty years

a power-law distribution..you can forecast the number of large-scale events from the number of small-scale ones, or vice versa

first, people start to mistake the noise for a signal. second, this noise pollutes journals, blogs, and news accounts with false alarms, undermining good science and setting back our ability to understand how the system really works

if you feed a computer a string of coin tosses (a random mix of 1's and 0's representing heads and tails), and then test out statistical parameters to try to fit a pattern-matching model, eventually it will think it can call 60 percent or 70 percent or (if you include enough variables) 100 percent of coin flips correctly. all this is artificial, of course; over the long run, it will call exactly 50 percent of coin flips correctly, no more and no less

there are more possible chess games than the number of atoms in the universe

in any long game of chess, it is quite likely that you and your opponent will eventually reach some position that literally no two players in the history of humanity have encountered before

if you doubt the practical uses of bayes's theorem, you have probably never witnessed a poker game

any investor can do as well as the average investor with almost no effort

the distribution of stock-market crashes can also be modeled fairly well by a power-law distribution, which is the same function that governs the frequency of earthquakes

suppose, for instance, that you had attempted to make a climate forecast based on an extremely simple statistical model: one that looked solely at co2 levels and temperatures, and extrapolated a prediction from these variables alone, ignoring sulfer and enso and sunspots and everything else. this wouldn't require a supercomputer; it could be calculated in a few microseconds on a laptop. how accurate would such a prediction have been?in fact, it would have been very accurate-quite a bit better, actually, than the ipcc's forecast. if you had placed the temperature record from 1850 through 1989 into a simple linear regression equation, along with the level of co2 as measured in antarctic ice cores and at the mauna loa observatory in hawaii, it would have predicted a global temperature increase at the rate of 1.5c per century from 1990 through today, exactly in line with the actual figure

even if you fly twenty times per year, you are about twice as likely to be struck by lightning

what isn't acceptable under bayes's theorem is to pretend that you don't have any prior beliefs. you should work to reduce your biases, but to say you have none is a sign that you have many. to state your beliefs up front- to say "here's where i'm coming from" -is a way to operate in good faith and to recognize that you perceive reality through a subjective filter